distilbert-lolchamps

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.6389

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss
2.7704	1.0	81	2.3357
2.3018	2.0	162	2.1004
2.1364	3.0	243	1.9746
2.0045	4.0	324	1.8978
1.9227	5.0	405	1.8303
1.8589	6.0	486	1.7865
1.8129	7.0	567	1.7097
1.7781	8.0	648	1.7250
1.754	9.0	729	1.6804
1.7308	10.0	810	1.6659
1.7039	11.0	891	1.6875
1.6905	12.0	972	1.6248
1.6819	13.0	1053	1.6169
1.6828	14.0	1134	1.6596
1.6722	15.0	1215	1.6389

Framework versions

• Transformers 4.39.3
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.15.2